cadminer:一个挖掘消费者不良药物副作用报告的系统

Sarvnaz Karimi, Alejandro Metke-Jimenez, Anthony N. Nguyen
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引用次数: 10

摘要

我们推出了CADEminer,这是一个挖掘消费者对药物评论的系统,以促进发现临床试验中可能未发现的药物副作用。CADEminer利用搜索和自然语言处理技术(a)提取评论中提到的副作用和其他相关概念,如药物名称和疾病;(b)将提取的提及归一化到它们在本体(如SNOMED CT和MedDRA)中的统一表示;(c)确定所提取概念之间的关系,例如药物引起的副作用;(d)查阅已知药物副作用的权威清单,以确定所提取的副作用是否是新的,因而需要进一步调查;最后(e)提供数据的统计和可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CADEminer: A System for Mining Consumer Reports on Adverse Drug Side Effects
We introduce CADEminer, a system that mines consumer reviews on medications in order to facilitate discovery of drug side effects that may not have been identified in clinical trials. CADEminer utilises search and natural language processing techniques to (a) extract mentions of side effects, and other relevant concepts such as drug names and diseases in reviews; (b) normalise the extracted mentions to their unified representation in ontologies such as SNOMED CT and MedDRA; (c) identify relationships between extracted concepts, such as a drug caused a side effect; (d) search in authoritative lists of known drug side effects to identify whether or not the extracted side effects are new and therefore require further investigation; and finally (e) provide statistics and visualisation of the data.
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